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Overset grid applications on distributed memory MIMD computers

Analysis of modern aerospace vehicles requires the computation of flowfields about complex three dimensional geometries composed of regions with varying spatial resolution requirements. Overset grid methods allow the use of proven structured grid flow solvers to address the twin issues of geometrical complexity and the resolution variation by decomposing the complex physical domain into a collection of overlapping subdomains. This flexibility is accompanied by the need for irregular intergrid boundary communication among the overlapping component grids. This study investigates a strategy for implementing such a static overset grid implicit flow solver on distributed memory, MIMD computers; i.e., the 128 node Intel iPSC/860 and the 208 node Intel Paragon. Performance data for two composite grid configurations characteristic of those encountered in present day aerodynamic analysis are also presented.

Chawla, Kalpana↗

Time Sequence Machine Learning-Based Data Intrusion Detection for Smart Voltage Source Converter-Enabled Power Grid

Smart inverters of distributed energy resources can enable cloud computing, condition monitoring, result visualization, remote control, and peer-to-peer energy trading in advanced power systems. However, the advent of data injection attacks in the communication architecture can alter measurement characteristics of power grids and have devastating consequences. In this article, we propose a time sequence machine learning-based anomaly detection methodology for detecting cyber intrusion into control signal setpoints and dc voltage signal measurement bias of the voltage source converter (VSC) in wind generators. We first investigated the effects of four types of denial of service, tampering signal, and stealthy-type data intrusion attacks on smart VSCs and overall wind farms. We then proposed a novel time sequence machine learning-based intrusion detection framework that can be implemented to detect different cyberattacks in the VSCs. The performance of the proposed framework has been compared with that of autoencoder and clustering-based intrusion detection framework. The proposed framework was validated by using the IEEE 39 bus power system in the presence of four wind farms in different locations. Using several metrics for intrusion detection performance, we validated the effectiveness of the proposed framework.

42 ENGINEERING↗

Land use change detection based on multi-date imagery from different satellite sensor systems

An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

Stow, Douglas A.↗

Validation for the Tropical Rainfall Measuring Mission: Lessons Learned and Future Plans

The Tropical Rainfall Measuring Mission (TRMM) was launched in November 1997 and is a highly regarded and successful mission. A major component of the TRMM program was its Ground Validation (GV) program. Through dedicated research and hard work by many groups, both the GV and satellite-retrieved rain estimates have shown a convergence at key GV sites, lending credibility to the global TRMM estimates. To be sure, there are some regional differences between the various satellite estimates themselves, which still need to be addressed; however, it can be said with some certainty that TRMM has provided a high-quality, long-term climatological data set for researchers that provides errors on the order of 10-20%, rather than pre-TRMM era error estimates on the order of 50-100%. The TRMM GV program's main operational task is to provide rainfall products for four sites: Darwin, Australia (DARW); Houston, Texas (HSTN); Kwajalein, Republic of the Marshall Islands (KWAJ); and, Melbourne, Florida (MELB). A comparison between TRMM Ground Validation (Version 5) and Satellite (Version 6) rain intensity estimates is presented. The gridded satellite product (3668) will be compared to GV Level II rain-intensity and -type maps (2A53 and 2A54, respectively). The 3G68 product represents a 0.5 deg x 0.5 deg data grid providing estimates of rain intensities from the TRMM Precipitation Radar (PR), Microwave Imager (TMI) and Combined (COM) algorithms. The comparisons will be sub-setted according to geographical type (land, coast and ocean). The convergence of the GV and satellite estimates bodes well for expectations for the proposed Global Precipitation Measurement (GPM) program and this study and others are being leveraged towards planning GV goals for GPM. A discussion of lessons learned and future plans for TRMM GV in planning for GPM will also be provided.

Wolff, David B.↗

Ambient-Frequency-Data Based System-Level Inertia Estimation Using Physical Equation and its Practice on Hawaii Islands

Here, in this paper, a practical ambient-frequency-data-based inertia estimation method using a physical equation is proposed and validated by real measurement data from Hawaii island grids. With high renewable penetration, accurate inertia estimation is important and urgent. Ambient frequency oscillation always exists in power grids, so the proposed method has advantages of real-time inertia estimation and no need for additional disturbances. This paper first developed the physical equation for inertia estimation to offer a clear mechanism for easy implementation in practice. To apply the proposed method in actual grids, a practical method to extract the ambient frequency oscillation from frequency measurement is further proposed. The inertia estimation using the physical equation is validated by KIUC simulation data and HECO field data, in which error rates are around 2% and 8%, respectively. Practical inertia estimation is challenging due to the large amounts of resources contributing to the power grid's effective inertia, but the method provided in this paper can offer a novel way for practical inertia estimation, which can help renewable penetration to boost carbon-free grid.

14 SOLAR ENERGY↗

A Robust Event Diagnostics Platform: Integrating Tensor Analytics and Machine Learning into Real-time Grid Monitoring

The objective of this project is to develop a robust event diagnostics (RED) platform by integrating state-of-the-art tensor analytics and machine learning into real-time grid monitoring. The proposed platform can effectively analyze and discover the information hiding within the provided PMU data for effective real-time grid monitoring. The proposed RED platform provides a set of robust diagnostics tools for grid operation and management, including 1) data quality assessment, 2) data completion, 3) event detection, and 4) robust event classification. All the functionalities of the RED platform can help the operator to make informed decisions and respond in a timely manner. The developed RED platform will serve as an innovative advisory tool to reliably identify key events and discover new insights about the events and grid characteristics in the PMU data, and contribute to the efficient, safe, reliable operation and design of the nation’s electric system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Artificial Intelligence Techniques in Smart Grid: A Survey

The smart grid is enabling the collection of massive amounts of high-dimensional and multi-type data about the electric power grid operations, by integrating advanced metering infrastructure, control technologies, and communication technologies. However, the traditional modeling, optimization, and control technologies have many limitations in processing the data; thus, the applications of artificial intelligence (AI) techniques in the smart grid are becoming more apparent. This survey presents a structured review of the existing research into some common AI techniques applied to load forecasting, power grid stability assessment, faults detection, and security problems in the smart grid and power systems. It also provides further research challenges for applying AI technologies to realize truly smart grid systems. Finally, this survey presents opportunities of applying AI to smart grid problems. The paper concludes that the applications of AI techniques can enhance and improve the reliability and resilience of smart grid systems.

energy systems↗

Spatial and Temporal Uncertainty of Crop Yield Aggregations

The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.

Aggregation uncertainty↗

CODARcode/MGARD

MGARD is a software providing error-controlled lossy compression and data refactoring based on multi-grid theories. It transforms floating-point scientific data into a multilevel representation, followed by quantization and lossless encoding processes, resulting in a self-describing compressed buffer. It supports diverse data topologies, error control norms, and computing architectures.

Chen, Jieyang [University of Oregon]↗

The relative contributions of increased resolution in the data assimilation and in the forecast model to satellite data impact

Assimilation cycles were carried out with two versions of the GLAS second order GCM: a coarse version with 4 deg latitude by 5 deg longitude resolution, called the C model, and a fine version with 2.5 deg latitude by 3 deg longitude resolution called the F model. For the two DST-6 cases where the combined influence of satellite data and model resolution are at a maximum at sea level, the relative contributions of increased resolution in the data assimilation and in the forecast models were evaluated. F model forecasts were generated from the C model SAT assimilation interpolated by the F grid, and C model forecasts were generated from the F model SAT assimilation interpolated to the C grid. These forecasts were then compared with the corresponding forecasts which had utilized the same grid resolution in the data assimilation and forecast models, CS and FS.

Atlas, R.↗

Improving Access to Precipitation Data for GIS Users: Designing for Ease of Use

The Global Precipitation Measurement Mission (GPM) is a NASA/JAXA led international mission to configure a constellation of space-based radiometers to monitor precipitation over the globe. The GPM goal of making global 3-hour precipitation products available in near real-time will make such global products more useful to a broader community of modelers and Geographic Information Systems (GIS) users than is currently the case with remote sensed precipitation products. Based on the existing interest to make Tropical Rainfall Measuring Mission (TRMM) data available to a growing community of GIS users as well as what will certainly be an expanded community during the GPM era, it is clear that data systems must make a greater effort to provide data in formats easily used by GIS. We describe precipitation GIS products being developed for TRMM data. These products will serve as prototypes for production efforts during the GPM era. We describe efforts to convert TRMM precipitation data to GeoTIFF, Shapefile, and ASCII grid. Clearly, our goal is to format GPM data so that it can be easily used within GIS applications. We desire feedback on these efforts and any additions or direction changes that should be undertaken by the data system.

Stocker, Erich F.↗

Translator for Optimizing Fluid-Handling Components

A software interface has been devised to facilitate optimization of the shapes of valves, elbows, fittings, and other components used to handle fluids under extreme conditions. This software interface translates data files generated by PLOT3D (a NASA grid-based plotting-and- data-display program) and by computational fluid dynamics (CFD) software into a format in which the files can be read by Sculptor, which is a shape-deformation- and-optimization program. Sculptor enables the user to interactively, smoothly, and arbitrarily deform the surfaces and volumes in two- and three-dimensional CFD models. Sculptor also includes design-optimization algorithms that can be used in conjunction with the arbitrary-shape-deformation components to perform automatic shape optimization. In the optimization process, the output of the CFD software is used as feedback while the optimizer strives to satisfy design criteria that could include, for example, improved values of pressure loss, velocity, flow quality, mass flow, etc.

Landon, Mark↗

High resolution wind measurements for offshore wind energy development

A method, apparatus, system, article of manufacture, and computer readable storage medium provide the ability to measure wind. Data at a first resolution (i.e., low resolution data) is collected by a satellite scatterometer. Thin slices of the data are determined. A collocation of the data slices are determined at each grid cell center to obtain ensembles of collocated data slices. Each ensemble of collocated data slices is decomposed into a mean part and a fluctuating part. The data is reconstructed at a second resolution from the mean part and a residue of the fluctuating part. A wind measurement is determined from the data at the second resolution using a wind model function. A description of the wind measurement is output.

Nghiem, Son Van↗

A regional analysis of cloudy mean spherical albedo over the marine stratocumulus region and the tropical Atlantic Ocean

Since clouds are the largest variable in Earth's radiation budget, it is critical to determine both the spatial and temporal characteristics of their radiative properties. The relationships between cloud properties and cloud fraction are studied in order to supplement grid scale parameterizations. The satellite data used is from three hourly ISCCP (International Satellite Cloud Climatology Project) and monthly ERBE (Earth Radiation Budget Experiment) data on a 2.5 deg x 2.5 deg latitude-longitude grid. Mean cloud spherical albedo, the mean optical depth distribution, and cloud fraction are examined and compared off the coast of California and the mid-tropical Atlantic for July 1987 and 1988. Individual grid boxes and spatial averages over several grid boxes are correlated to Coakley's theory of reflection for uniform and broken layered cloud and to Kedem, et al.'s findings that rainfall volume and fractional area of rain in convective systems is linear. Kedem's hypothesis can be expressed in terms of cloud properties. That is, the total volume of liquid in a box is a linear function of cloud fraction. Results for the marine stratocumulus regime indicate that albedo is often invariant for cloud fractions of 20% to 80%. Coakley's satellite model of small and large clouds with cores (1 km) and edges (100 m) is consistent with this observation. The cores maintain high liquid water concentrations and large droplets while the edges contain low liquid water concentrations and small droplets. Large clouds are just a collection of cores. The mean optical depth (TAU) distributions support the above observation with TAU values of 3.55 to 9.38 favored across all cloud fractions. From these results, a method based upon Kedem, et al's theory is proposed to separate the cloud fraction and liquid water path (LWP) calculations in a general circulation model (GCM). In terms of spatial averaging, a linear relationship between albedo and cloud fraction is observed. For tropical locations outside the Intertropical Convergence Zone (ITCZ), results of cloud fraction and albedo spatial averaging followed that of the stratus boxes containing few overcast scenes. Both the ideas of Coakley and Kedem, et al. apply. Within the ITCZ, the grid boxes tended to have the same statistical properties as stratus boxes containing many overcast scenes. Because different dynamical forcing mechanisms are present, it is difficult to devise a method for determining subgrid scale variations. Neither of the theories proposed by Kedem, et al. or Coakley works well for the boxes with numerous overcast scenes.

Ginger, Kathryn M.↗

[Low-Frequency Flow Oscillation

The results of the research conducted under this grant are presented in detail in three Master theses, by Heinrich, Balow, and Broeren. Additional analysis of the experimental data can be found in two AIAA Journal articles and two conference papers. Citations for all of the studies' publications can be found in the bibliography which is attached. The objective of Heinrich's study was to document the low-frequency flow oscillation on the LRN-1007 airfoil, which had been previously observed at low Reynolds number, to determine its origin, and explore the phenomenon at higher Reynolds number. Heinrich performed detailed flow visualization on the airfoil using surface fluorescent oil and laser-sheet off-body visualization. A large leading-edge separation bubble and trailing-edge separation was identified on the airfoil just prior to the onset of the unsteady stall flow oscillation. From the laser-sheet data, the unsteady flow appeared as a massive boundary-layer separation followed by flow reattachment. Hot-wire data were taken in the wake to identify the presence of the flow oscillation and the dominant frequency. The oscillation was found in the flow from a Reynolds number of 0.3 to 1.3 x 10 exp 6. The Strouhal number based on airfoil projected height was nominally 0.02 and increased slightly with increasing Reynolds number and significantly with increasing airfoil angle of attack. Balow focused his research on the leading-edge separation bubble which was hypothesized to be the origin of the low-frequency oscillation. Initially, experimental measurements in the bubble at the onset of the low-frequency oscillation were attempted to study the characteristics of the bubble and explain possible relationships to the shear-layer-flapping phenomena. Unfortunately, the bubble proved to be extremely sensitive to the probe interference and it drastically reduced the size of the bubble. These detailed measurements were then abandoned by Balow. However, this led to a series of tests where the leading-edge bubble and trailing-edge separation were altered and the affect on the flow-oscillation studied. Balow found that by tripping the airfoil boundary-layer with "zigzag" tape ahead of bubble separation, the bubble was effectively eliminated mid the oscillation suppressed. Wake survey drag measurements showed a drastic reduction in airfoil drag when the bubble and oscillation were eliminated. Using the "zigzag" tape, the trailing-edge separation was moved downstream approximately 5 percent chord. This was found to reduce the amplitude of the oscillation, particularly in the onset stage at low angle of attack (around 14 degrees). Through detailed analysis of the wake behind the airfoil during the unsteady flow oscillation, Balow provided a better understanding of the wake flowfield. Broeren studied the oscillating flowfield in detail at Reynolds number equal 3 x 10 exp 5 and an angle of attack of 15 degrees using laser Doppler velocimetry (LDV). Two-dimensional LDV data were acquired at 687 grid points above the model upper surface while hot-wire data were taken simultaneously in the wake. Using the hot-wire signal, the LDV data were phase averaged into 24 bins to represent a single ensemble average of one oscillation cycle. The velocity data showed a flowfield oscillation that could be divided into three flow regimes. In the first regime, the flow over the airfoil was completely separated initially, the flowfield reattached from the leading edge and the reattachment point moved downstream with increasing time or phase. Broeren referred to this as the reattachment regime. The bubble development regime followed, where a leading-edge separation bubble formed at the leading edge and grew with increasing time. During the initial part of this regime the trailing-edge separation continued to move downstream. However, during the last 30 degrees of phase the trailing-edge separation moved rapidly forward and appeared to merge with the leading-edge bubble. During the third regime, the separation regime, the flow was segmented from the airfoil leading edge and did not reattach to the airfoil surface. The reverse flow was seen to grow in vertical extent up from the model surface as the phase increased. Next reattachment began again at the leading edge signaling the start of the reattachment regime, and so the cycle continued. From Broeren's work, the details of the unsteady flowfield over the airfoil were seen for the first time. From this research a great deal has been learned about the low-frequency flow oscillation which naturally occurs on the LRN-1007 airfoil near stall. The oscillation was seen to persist at higher Reynolds number, the dependence of the Strouhal number on angle of attack and Reynolds number were discovered, the critical role played by the laminar bubble was shown and the entire upper surface flowfield during a flow oscillation cycle was measured and analyzed. What still eludes understanding is the scaling of the flow oscillation and why certain airfoils, such as the LRN, have a very strong low-frequency mode and other airfoils exhibit no organized low-frequency oscillation at all.

Bragg, Michael B.↗

CHESS 2025: Orthorectified airborne RGB imagery from NEON AOP surveys

This dataset provides Level 1 (L1) and Level 3 (L3) orthorectified Red-Green-Blue (RGB) imagery collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). This high-resolution imagery is a photographic record of red, green, and blue visible light from sunlight reflected off of the Earth’s surface. The data comprise full-color images of the ground surface and are primarily intended to provide context to imaging spectroscopy and light detection and ranging (LiDAR) data. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. RGB images were acquired using the PhaseOne IXM-RS150F high-resolution digital camera onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). The package data include both an L1 product comprising one camera frame per file and an L3 mosaic aligned to the Universal Transverse Mercator (UTM) Zone 13N grid and the World Geodetic System (WGS) 84 projection. Both products are provided in geotif (.tif) format at 0.1 m ground resolution. The bulk of the imagery was collected during the main CHESS field campaign from June 13 to July 15, 2025. Additional images of a portion of the Upper Taylor (UPTA) domain were collected on September 18, 2025, to fill gaps in imagery identified after the main campaign was complete. RGB camera imagery is not radiometrically calibrated, and therefore pixel values should not be exploited for scientific analysis. Pixel values have undergone a manual adjustment to enhance feature identification. The imagery is rigorously geolocated which does allow for reliable geometric information to be retrieved. To generate the orthorectified imagery, the NEON AOP camera captured visible spectrum in red, green, and blue bands. The raw images were then processed using NEON’s camera orthorectification workflow. A boresight calibration flight was made to build a complete camera, distortion, and alignment model. Color balance/white balance and exposure correction were applied to the raw RGB images. The corrected images were orthorectified by ray-tracing image pixels to a lidar-derived digital surface model (DSM) mesh using the refined camera model, outputting orthorectified raster pixels on a regular grid. Flightline-level data were mosaicked by selecting per-pixel contributions from overlapping orthorectified images using line-of-sight (LOS) zenith angle minimization to reduce edge distortions. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

The State of NASA's Information Power Grid

This viewgraph presentation transfers the concept of the power grid to information sharing in the NASA community. An information grid of this sort would be characterized as comprising tools, middleware, and services for the facilitation of interoperability, distribution of new technologies, human collaboration, and data management. While a grid would increase the ability of information sharing, it would not necessitate it. The onus of utilizing the grid would rest with the users.

Johnston, William E.↗

Jitter Controller Software

Sinusoidal jitter is produced by simply modulating a clock frequency sinusoidally with a given frequency and amplitude. But this can be expressed as phase jitter, frequency jitter, or cycle-to-cycle jitter, rms or peak, absolute units, or normalized to the base clock frequency. Jitter using other waveforms requires calculating and downloading these waveforms to an arbitrary waveform generator, and helping the user manage relationships among phase jitter crest factor, frequency jitter crest factor, and cycle-to-cycle jitter (CCJ) crest factor. Software was developed for managing these relationships, automatically configuring the generator, and saving test results documentation. Tighter management of clock jitter and jitter sensitivity is required by new codes that further extend the already high performance of space communication links, completely correcting symbol error rates higher than 10 percent, and therefore typically requiring demodulation and symbol synchronization hardware to operating at signal-to-noise ratios of less than one. To accomplish this, greater demands are also made on transmitter performance, and measurement techniques are needed to confirm performance. It was discovered early that sinusoidal jitter can be stepped on a grid such that one can connect points by constant phase jitter, constant frequency jitter, or constant cycle-cycle jitter. The tool automates adherence to a grid while also allowing adjustments off-grid. Also, the jitter can be set by the user on any dimension and the others are calculated. The calculations are all recorded, allowing the data to be rapidly plotted or re-plotted against different interpretations just by changing pointers to columns. A key advantage is taking data on a carefully controlled grid, which allowed a single data set to be post-analyzed many different ways. Another innovation was building a software tool to provide very tight coupling between the generator and the recorded data product, and the operator's worksheet. Together, these allowed the operator to sweep the jitter stimulus quickly along any of three dimensions and focus on the response of the system under test (response was jitter transfer ratio, or performance degradation to the symbol or codeword error rate). Additionally, managing multi-tone and noise waveforms automated a tedious manual process, and provided almost instantaneous decision- making control over test flow. The code was written in LabVIEW, and calls Agilent instrument drivers to write to the generator hardware.

Lansdowne, Chatwin↗